multiple-inputmultiple-output (MIMO) techniques are now being commonplace in wireless communication systems as they provide diversity and spatial multiplexing gains compared to single-input single-output (SISO) syste...
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ISBN:
(纸本)9781509017508
multiple-inputmultiple-output (MIMO) techniques are now being commonplace in wireless communication systems as they provide diversity and spatial multiplexing gains compared to single-input single-output (SISO) systems. Due to the induced high complexity of maximum likelihood (ML) detection for MIMO systems, suboptimal detection is usually employed but at a performance loss. This loss has been fully characterized for linear receivers, namely, zero-forcing (ZF) and minimum mean square error (MMSE) detectors. Interestingly, it has been noticed that in case of coding across transmit antennas, the MMSE receiver showed significant improvement over ZF in terms of outage probability at low spectral efficiencies, whereas for high spectral efficiencies, both receivers showed similar behaviour. We fill the gap between the two extreme cases (i.e., ML and linear receivers) through relaxing the linearity constraint by considering group receivers (viz. group zero-forcing (GZF) and group minimum mean square error (GMMSE) detectors) with coding across transmit antennas. We first derive the diversity-multiplexing tradeoff (DMT) for those group detectors. Next, we characterize the peculiar rate-dependent outage behaviour of the GMMSE, where it is found that tolerating additional detection complexity provides performance advantage w.r.t the MMSE at specific ranges of spectral efficiency. We corroborate our theoretical analysis via numerical simulations.
Along with the growing increase of the demand for establishing a safe and fast connection between different users,for the purpose of transferring large audio-visual data using a wireless technology,a great number of s...
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Along with the growing increase of the demand for establishing a safe and fast connection between different users,for the purpose of transferring large audio-visual data using a wireless technology,a great number of studies have been carried out on the multiple-inputmultiple-output Orthogonal Frequency-Division multiplexing *** the algorithm presented in this article,first a simple,but efficient,model for multiple-inputmultiple-output orthogonal frequency-division multiplexing systems is ***,where the Channel state matrix in the Transmitter is known to us,we have tried to find a desirable capacity for such a system,putting the discussions of the information theory into practice as well as applying the method of singular value decomposition in channel *** simulation results prove such a claim.
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